Meteorology-driven PM2.5 interannual variability over East Asia

Atmospheric fine particulate matter (PM2.5) is a human health risk factor, but its ambient concentration depends on both precursor emissions and meteorology. While emission reductions are used to set PM2.5-related health policies, the effect of meteorology is often overlooked. To explore this aspect, we examined PM2.5 interannual variability (IAV) associated with meteorological parameters using the long-term simulation from the Community Earth System Model (CESM1), a global climate-chemistry model, with fixed emissions. The results are subsequently contrasted with the MERRA-2 reanalysis dataset, which inherently considers emission and meteorology effects. Over continental East Asia, the CESM1 domain-average PM2.5 IAV is 6.7 %, mainly attributed to humidity, precipitation, and ventilation variation. The grid-cell PM2.5 IAVs over southern East China are larger, up to 12 % due to the more substantial influence of El Niño-induced meteorological anomalies. Under such climate extreme, sub-regional PM2.5 concentration may occasionally exceed WHO air quality guideline levels despite the compliance of the long-term mean. The simulated PM2.5 IAV over continental East Asia is ~25 % of that derived from the MERRA-2 data, which highlights the influence of both emission and meteorology-driven variations and trends inherent in the latter. Although emission-driven variability is significant to PM2.5 IAV, in remote areas downwind of major source regions in East Asia, North America, and Western Europe, the MERRA-2 data revealed that meteorological variations contributed more to PM2.5 IAV than emission variations. Thus, when setting policies for complying with the WHO PM2.5-related air quality guideline levels, the highest annual PM2.5 associated with climate extremes should be considered instead of that based on average climate conditions.

Sensitivity of PM2.5 and O3 pollution episodes to meteorological factors over the North China Plain

The Comprehensive Air-quality Model with extensions (CAMx) was used to explore the sensitivity of PM_2.5 and O₃ concentrations to four selected meteorological factors: wind speed, temperature, water vapor mixing ratio (Q), and planetary boundary layer height (PBLH) during two pollution episodes over the North China Plain (NCP). We also investigated the impact pathways of different meteorological factors on the formation of PM_2.5 and O_3. It is found that PM_2.5 was more sensitive to the selected meteorological factors in the southeastern NCP, where high anthropogenic emissions and severe air pollution occur. Large variations were observed along the Taihang Mountains, where the height of the terrain changes dramatically. The sensitivity of O₃ to wind speed, PBLH, temperature, and Q was mainly determined by the inhibition effects of PM_2.5 in winter, while in summer, the complex chemical reactions were dominant. Significant diurnal variations of process analysis (PA) results were observed under various meteorological conditions. Higher temperature generally enhance heterogeneous chemistry and transport of NO₃^- through the top boundary layer during night-time in winter, however, in summer, the heterogeneous chemistry of NO₃^- and NH₄⁺ during daytime were the major pathways to the increased PM_2.5 due to increased temperature. Moreover, temperature alter PM_2.5 concentrations through affecting vertical diffusivity and relative humidity, and alter O₃ concentrations by affecting the gas phase chemistry and mass fluxes through the top boundary layer. Q mainly affects the rate of chemical reactions of PM_2.5 and O₃. The different impact pathways suggest that it is essential to consider variations in meteorological factors, in addition to the direct impacts of wind speed and PBLH, more attention should be paid to the complex impacts of temperature and Q, when developing emission control strategies.